{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T11:48:21Z","timestamp":1782992901210,"version":"3.54.5"},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2021,11,27]],"date-time":"2021-11-27T00:00:00Z","timestamp":1637971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Solubility and expression levels of proteins can be a limiting factor for large-scale studies and industrial production. By determining the solubility and expression directly from the protein sequence, the success rate of wet-lab experiments can be increased.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this study, we focus on predicting the solubility and usability for purification of proteins expressed in Escherichia coli directly from the sequence. Our model NetSolP is based on deep learning protein language models called transformers and we show that it achieves state-of-the-art performance and improves extrapolation across datasets. As we find current methods are built on biased datasets, we curate existing datasets by using strict sequence-identity partitioning and ensure that there is minimal bias in the sequences.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The predictor and data are available at https:\/\/services.healthtech.dtu.dk\/service.php?NetSolP and the open-sourced code is available at https:\/\/github.com\/tvinet\/NetSolP-1.0.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab801","type":"journal-article","created":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T16:17:05Z","timestamp":1637684225000},"page":"941-946","source":"Crossref","is-referenced-by-count":113,"title":["NetSolP: predicting protein solubility in\n                    <i>Escherichia coli<\/i>\n                    using language models"],"prefix":"10.1093","volume":"38","author":[{"given":"Vineet","family":"Thumuluri","sequence":"first","affiliation":[{"name":"Indian Institute of Technology Madras , India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hannah-Marie","family":"Martiny","sequence":"additional","affiliation":[{"name":"Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark , Lyngby 2800, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0111-1362","authenticated-orcid":false,"given":"Jose J","family":"Almagro Armenteros","sequence":"additional","affiliation":[{"name":"Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen , 2200 Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jesper","family":"Salomon","sequence":"additional","affiliation":[{"name":"Enzyme Research , Novozymes A\/S, Lyngby 2800, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9412-9643","authenticated-orcid":false,"given":"Henrik","family":"Nielsen","sequence":"additional","affiliation":[{"name":"Department of Health Technology, Technical University of Denmark , Lyngby 2800, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4993-7916","authenticated-orcid":false,"given":"Alexander Rosenberg","family":"Johansen","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Stanford University , Stanford, CA 94305, USA"},{"name":"Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,11,27]]},"reference":[{"key":"2023020108532373600_btab801-B1","author":"Berman","year":"2017"},{"key":"2023020108532373600_btab801-B2","doi-asserted-by":"crossref","first-page":"4691","DOI":"10.1093\/bioinformatics\/btaa578","article-title":"Solubility-weighted index: fast and accurate prediction of protein solubility","volume":"36","author":"Bhandari","year":"2020","journal-title":"Bioinformatics"},{"key":"2023020108532373600_btab801-B3","author":"Brandes","year":"2021"},{"key":"2023020108532373600_btab801-B4","doi-asserted-by":"crossref","first-page":"1875","DOI":"10.1093\/bioinformatics\/btm270","article-title":"Predicting functionally important residues from sequence conservation","volume":"23","author":"Capra","year":"2007","journal-title":"Bioinformatics"},{"key":"2023020108532373600_btab801-B5","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1093\/bib\/bbt057","article-title":"Bioinformatics approaches for improved recombinant protein production in Escherichia coli: protein solubility prediction","volume":"15","author":"Chang","year":"2014","journal-title":"Brief. 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